Fusion of automatic target recognition algorithims

Syed A. Rizvi; Nasser M. Nasrabadi

doi:10.1117/12.477018

25 July 2002 Fusion of automatic target recognition algorithims

Syed A. Rizvi, Nasser M. Nasrabadi

Proceedings Volume 4726, Automatic Target Recognition XII; (2002) https://doi.org/10.1117/12.477018
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

In this paper, we investigate several fusion techniques for designing a composite classifier to improve the performance (probability of correct classification) of FLIR ATR. The motivation behind the fusion of ATR algorithms is that if each contributing technique in a fusion algorithm composite classifier) emphasizes on learning at least some features of the targets that are not learned by other contributing techniques for making a classification decision, a fusion of ATR algorithms may improve overall probability of correct classification of the composite classifier. In this research, we propose to use four ATR algorithms for fusion. We propose to use averaged Bayes classifier, committee of experts, stacked-generalization, winner-takes-all, and ranking-based fusion techniques for designing the composite classifiers. The experimental results show an improvement of more than 5 % over the best individual performance.

Citation Download Citation

Syed A. Rizvi and Nasser M. Nasrabadi "Fusion of automatic target recognition algorithims", Proc. SPIE 4726, Automatic Target Recognition XII, (25 July 2002); https://doi.org/10.1117/12.477018

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